Cloud Support Engineer

About the Role

Cloud Support Engineer

You will work closely with developers, DevOps, and data engineering teams to ensure high availability, scalability, and performance of our containerized and data-driven applications.

Key Responsibilities

• Cloud Infrastructure Support:

• Manage and support workloads running on

  Google Cloud Platform (GCP)

  , primarily using

  GKE

  .
• Monitor and maintain clusters, nodes, and deployments for optimal performance.
  

• Kubernetes Operations:

• Handle deployment, scaling, and troubleshooting of containerized applications.
• Implement and maintain CI/CD pipelines integrated with Kubernetes.
• Define and enforce Kubernetes resource limits, namespaces, and policies.
  

• Data Pipelines & Workflow Support:

• Support and optimize

  data ingestion and transformation pipelines

  (e.g., using Apache Beam, Dataflow, Airflow, or similar tools).
• Monitor job executions, troubleshoot failures, and ensure timely data delivery.
  

• Automation & Observability:

• Implement monitoring, alerting, and logging solutions (e.g.,

  Prometheus, Grafana, Stackdriver, ELK

  ).Automate repetitive tasks using scripts and infrastructure-as-code (e.g., Terraform, Helm).

• Incident Management & Root Cause Analysis:

• Respond to production incidents and work on prevention measures.
  Collaborate with engineering teams to drive long-term reliability improvements.

Required Skills & Experience

• Strong experience with

  Kubernetes

  and

  GKE

  in production environments.
• Experience in GCP.
• Solid understanding of

  containerization (Docker)

  and

  microservice architectures

  .
• Hands-on experience in

  data pipeline management

  (Airflow, Dataflow, Beam, or equivalent).
• Knowledge of

  CI/CD tools

  (Jenkins, GitLab CI, Cloud Build, ArgoCD).
• Experience with

  monitoring and logging

  tools such as Prometheus, Grafana, or Stackdriver.
• Familiarity with

  Terraform

  ,

  Helm

  , or other IaC tools.Good understanding of

  networking, load balancing, and security

  in cloud environments.
• Proficiency in

  Python, Bash, or Go

  for scripting and automation.

Preferred Qualifications

• GCP Professional Cloud Engineer

  or

  CKA (Certified Kubernetes Administrator)

  certification.
• Azure Cloud setup
• Exposure to

  multi-cloud

  or

  hybrid-cloud

  setups.
• Experience supporting

  real-time or batch data systems

  .
• Familiarity with

  DevOps

  and

  SRE

  principles.

Soft Skills

• Strong problem-solving and analytical skills.
• Ability to work collaboratively in cross-functional teams.
• Good communication and documentation skills.
• A proactive attitude towards learning and automation.